%0 Journal Article
%T 电商平台线上女装销售量的建模与预测<br> Modeling and Forecasting of Online Women’s Sales Volume in ECommerce Platform
%A 赵戎祥
%A 岳逸超
%A 刘思琪
%A 郑林涛
%A 杨金
%J Statistics and Applications
%P 404-419
%@ 2325-226X
%D 2019
%I Hans Publishing
%R 10.12677/SA.2019.82045
%X <div style=\"text-align:justify;\">
	<span style=\"font-size:14px;\">本文认为乐町、Only、太平鸟2014~2017年的销售量数据可以看成一个时间序列，首先通过时间序列的时序图判断其时间序列的类型，然后根据不同的类型对数据进行预处理，这里由于序列具有集群效应，进而通过取对数消除异方差性，然后依次提出初步的数学模型，进行线性拟合和残差拟合来建立残差自回归模型，通过对模型不断识别、拟合、检验和优化，建立最恰当的时间序列模型，得出销售量对数的预测值，并以此预测三个品牌的销售量未来半年的走势。<br />
This paper thinks that the sales data
of Rakumachi, Only, and Taiping Bird in 2014-2017 can be regarded as a time
series. First, the type of time series is determined by time series timing diagram.
Then, the data is preprocessed according to different types. Since the sequence
has a cluster effect, the heteroscedasticity is eliminated by taking the
logarithm. Then, a preliminary mathematical
model is proposed in turn, and linear fitting and residual fitting are
performed to build a residual autoregressive model. By establishing the most
appropriate time series model for the model to continuously identify, fit, test
and optimize, the predicted value of the logarithm of the sales volume
is obtained, and the sales volume of the three brands is predicted in the next
six months.</span> 
</div>
%K 电商平台，时间序列模型，时序图检验，线性拟合，预测<br> Electronic Business Platform
%K Time Series Model
%K Timing Chart Test
%K Linear Fit
%K Forecast
%U http://www.hanspub.org/journal/PaperInformation.aspx?PaperID=29922